4.6 Article

Long-term Traffic-related Air Pollutant Exposure and Amyotrophic Lateral Sclerosis Diagnosis in Denmark A Bayesian Hierarchical Analysis

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EPIDEMIOLOGY
卷 33, 期 6, 页码 757-766

出版社

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/EDE.0000000000001536

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资金

  1. NIEHS [K99 ES033742]
  2. Earth Institute post-doctoral research fellowship at Columbia University
  3. National Institute of Environmental Health Sciences (NIEHS) [R01 ES030616, R01 ES028805, R01 AG066793, R21 ES028472, P30 ES009089, P30 ES000002]

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This study found a high probability of a positive association between ALS diagnosis and elemental carbon concentration. There were negative associations for nitrogen oxides, carbon monoxide, and no association for non-elemental carbon fine particles. Further research is needed to understand the role of traffic-related air pollution in ALS pathogenesis.
Background: Amyotrophic lateral sclerosis (ALS) is a fatal neunxlegenerative disease. Limited evidence suggests ALS diagnosis may be associated with air pollution exposure and specifically traffic-related pollutants. Methods: In this population-based case-control study, we used 3,937 ALS cases from the Danish National Patient Register diagnosed during 1989-2013 and matched on age, sex, year of birth, and vital status to 19,333 population-based controls free of ALS at index date. We used validated predictions of elemental carbon (EC), nitrogen oxides (NOx), carbon monoxide (CO), and fine particles (PM2.5) to assign 1-, 5-, and 10-year average exposures pre-ALS diagnosis at study participants' present and historical residential addresses. We used an adjusted Bayesian hierarchical conditional logistic model to estimate individual pollutant associations and joint and average associations for traffic-related pollutants (EC, NOx, CO). Results: For a standard deviation (SD) increase in 5-year average concentrations, EC (SD = 0.42 mu g/m(3)) had a high probability of individual association with increased odds of ALS (11.5%; 95% credible interval - -1.0%, 25.6%; 96.3% posterior probability of positive association), with negative associations for NOx (SD - 20 mu g/m(3)) (-4.6%; 95% CrI = 18.1%, 8.9%; 27.8% posterior probability of positive association), CO (SD = 106 mu g/m(3)) (-3.2%; 95% CrI = 14.4%, 10.0%; 26.7% posterior probability of positive association), and a null association for nonclemcntal carbon fine particles (non-EC PM2.5) (SD = 2.37 mu g/m(3)) (0.7%; 95% CrI = 9.2%, 12.4%). We found no association between ALS and joint or average traffic pollution concentrations. Conclusions: This study found high probability of a positive association between ALS diagnosis and EC concentration. Further work is needed to understand the role of traffic-related air pollution in ALS pathogenesis.

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